Mapping and Modeling for Regional Planning

Size: px

Start display at page:

Download "Mapping and Modeling for Regional Planning"

Joleen Maxwell
5 years ago
Views:

1 Mapping and Modeling for Regional Planning Carol W. Witham Sacramento Valley Chapter California Native Plant Society contributors: David Ackerly John Dittes Julie Evens Josephine Guardino Robert F. Holland Todd Keeler-Wolf David King September 2006

2 Vegetation Mapping What constitutes a good vegetation map for use in regional planning?

3 Why do you need a vegetation map? Vegetation is considered to be the best single surrogate for more detailed habitat and ecosystem information. Geographic Information Systems (GIS) can be used to analyze vegetation and other environmental factors to help fill some of the data gaps and uncertainties related to species and habitat conservation.

4 Typical mapping exercises don t provide useful information A hypothetical land cover map, often referred to as a vegetation map. * Indicates rare plant occurrences.

5 Typical mapping exercises don t provide useful information How the typical planner and other stakeholders see vegetation.

6 Typical mapping exercises don t provide useful information What the typical planner and other stakeholders really see.

7 Why current mapping efforts don t work Planners write the contracts with the consultants who perform the mapping - or worse - have the mapping done in-house. Mapping is often based on keystone or listed species, usually animals. Most mapping is done from aerial imagery interpretation with no ground-truthing. No real data on ecosystem, processes, habitat, species or vegetation structure.

8 Why current mapping efforts don t work GIS jockeys often don t understand vegetation and only want to map what they can unambiguously distinguish from the aerial, generally land cover types. Mapping is limited by the resolution of the aerial imagery, the minimum mapping unit and the skills of the mapper. Time and money are often the most important considerations in planning efforts.

9 Integrated Vegetation Classification and Mapping - overview Stratify survey locations by variation in aerial imagery signatures. Collect field data. Classify vegetation based on field data.

10 Integrated Vegetation Classification and Mapping - overview Extrapolate vegetation classification from field data and identify similar units on aerial imagery. Ground-truth and refine as appropriate.

11 Integrated Vegetation Classification and Mapping - overview More detail in the vegetation map gives a better sense of why the rare plants occur where they do. * Indicates rare plant occurrences.

12 Integrated Vegetation Classification and Mapping - process Nested random sampling of vegetation in the planning region. Analysis and classification of vegetation setting the rules to play by. Extrapolation of field data to aerial imagery analysis and vegetation mapping. Attribute each map unit with factors such as canopy cover or disturbance. Ground-truth the map and refine.

13 Integrated Vegetation Classification and Mapping - benefits Links field data classification with mapping efforts. Standardizes methods and terms among agencies and between planning efforts. Provides more useful information on ecosystems, processes, habitats, species and vegetation structure. Can be used predictively to model habitat requirements of species.

14 Integrated Vegetation Classification and Mapping - drawbacks Planners and many consultants are uneducated as to the value of detailed vegetation classification and mapping. Often automatically rejected as too expensive and time consuming.* Most land within planning areas is not accessible for field data collection.** Fine-scale vegetation patterns cannot be mapped with existing aerial imagery.

15 Actual Example of Land Cover vs Vegetation Map Map A Land Cover Map 9 units Map B Vegetation Map 29 units from a small sample area of the San Diego mapping effort Courtesy of Julie Evens

16 How do we get from Map A to Map B? Planners and their consultants must be made aware of the conservation and economic benefits of accurate vegetation mapping. Good mapping allows predictive modeling. Good mapping facilitates tracking change over time. Good mapping upfront is less expensive than doing the maps over and over again. Conservationists must continue to advocate for the use of best available science in regional planning.

17 GIS Modeling What is it and how is it useful for regional planning?

18 GIS Modeling a very brief overview GIS software and other statistical analysis programs are used to compare one data set against another data set. Coarse-scale data sets are available for many environmental conditions (i.e. soils). Fine-scale data sets are developed through field survey work (i.e. CNDDB). Hypothesis can be developed and tested using these data sets.

19 GIS Modeling benefits and drawbacks It can be used to partially fill gaps and uncertainties that result from never having enough data to make decisions with absolute certainty. It can be used predictively and with historic data to detect change. It is modeling - a probability assessment and not exact science. It is only as good as your worst data layer and worst assumption.

20 Juncus leiospermus var. aharti

21 GIS Modeling to Predict Plant Biogeography CNDDB Records Soils/Geology Climate Data number crunching Elevation Slope Courtesy of Robert F. Holland

22 Jepson range: Elevation: < 1200 m. Bioregional distribution: Inner North Coast Ranges, Cascade Range Foothills, Sierra Nevada Foothills, Tehachapi Mountain Area, n San Joaquin Valley, San Francisco Bay Area, Inner South Coast Ranges, Western Transverse Ranges (n slope) Quercus douglasii

23 GIS Modeling to Predict Global Warming Range Shifts Courtesy of David Ackerly

24 Courtesy of Todd Keeler-Wolf Hulsea breviflora

Keeler-Wolf Geology Vegetation Types 0 to 3 Grids Overlapping 4 Grids

25 GIS Modeling to Predict Plant Population Locations Input Grids Modeling Results Elevation Soil Wetness Index Slope Number of Fires Courtesy of Todd Keeler-Wolf Geology Vegetation Types 0 to 3 Grids Overlapping 4 Grids Overlapping 5 Grids Overlapping 6 Grids Overlapping Species Found Search Area Trails Streams

26 Vernal Pools - a special case study Courtesy of David King

27 Vernal Pools - study challenges Vernal pool and grassland vegetation has not yet been adequately classified. Variations in vernal pool and grassland vegetation are too fine-scale to map. Most vernal pools are on private property and inaccessible for vegetation sampling. The South Sacramento HCP will cover ~344,000 acres of vernal pool grasslands.

28 Vernal Pools ecological assumptions Ecology and species composition can be correlated with pool size and hydrology. Hydrology and period of inundation can be correlated with pool size. Species diversity can be correlated with variability in pool size and hydrology. Ecological function can be correlated with pool interconnectivity. Landscape scale variability can be correlated with geology and soils.

GIS Modeling to Predict Highest Conservation Value Vernal Pool Area/Density Index Heads-up digitizing of all vernal pools within the study area. Overlay a random grid of 160 acre squares.

29 GIS Modeling to Predict Highest Conservation Value Vernal Pool Area/Density Index Heads-up digitizing of all vernal pools within the study area. Overlay a random grid of 160 acre squares. Calculate the acreage of vernal pools for each grid square. Tabulate the number of vernal pools for each grid square. Highest diversity is approximated by the areas that contain high acreage and/or high numbers of vernal pools. Courtesy of John Dittes & Josephine Guardino

30 GIS Modeling to Predict Highest Conservation Value Vernal Pool Area/Density Index Heads-up digitizing of all vernal pools within the study area. Overlay a random grid of 160 acre squares. Calculate the acreage of vernal pools for each grid square. Tabulate the number of vernal pools for each grid square. Highest diversity is approximated by the areas that contain high acreage and/or high numbers of vernal pools. Courtesy of John Dittes & Josephine Guardino

31 Summary What are the mapping and modeling take-home messages?

32 Take-home thoughts! Moving from Map A to Map B will require concerted efforts to educate planners on the benefits of good vegetation maps. Better vegetation maps are more cost effective in the long run and provide greater assurances for conservation. Modeling is a great tool, but depends on the quality of the data used for analyses.

33 We can t solve problems by using the same kind of thinking we used when we created them. - Albert Einstein

USE OF RADIOMETRICS IN SOIL SURVEY

USE OF RADIOMETRICS IN SOIL SURVEY Brian Tunstall 2003 Abstract The objectives and requirements with soil mapping are summarised. The capacities for different methods to address these objectives and requirements